Hepatocellular carcinoma (HCC) is one of the most common malignant tumors with poor prognosis. Epithelial–mesenchymal transition (EMT) is crucial for cancer progression and metastasis. Thus, we aimed to construct an EMT-related lncRNA signature for predicting the prognosis of HCC patients.Cox regression analysis and LASSO regression method were used to build an EMT-related lncRNAs risk signature based on TCGA database. Kaplan-Meier survival analysis was conducted to compare the overall survival (OS) in different risk groups. ROC curves and Cox proportional-hazards analysis were performed to evaluate the performance of the risk signature. RT-qPCR was conducted in HCC cell lines and tissue samples to detect the expression of some lncRNAs in this risk model. Furthermore, a nomogram involving the risk score and clinicopathological features was built and validated with calibration curves and ROC curves. In addition, we explored the association between risk signature and tumor immunity, somatic mutations status, and drugs sensitivity.Twelve EMT-related lncRNAs were obtained to construct the prognostic risk signature for patients with HCC. The Kaplan-Meier curve analysis revealed that patients in the high-risk group had worse overall survival (OS) than those in low-risk group. ROC curves and Cox regression analysis suggested the risk signature could predict HCC survival exactly and independently. The prognostic value of the risk model was confirmed in the testing and entire groups. We also found AC099850.3 and AC092171.2 were highly expressed in HCC cells and HCC tissues. The nomogram could accurately predict survival probability of HCC patients. Gene set enrichment analysis (GSEA) and gene ontology (GO) analysis showed that cancer-related pathways and cell division activity were enriched in high-risk group. The SNPs showed that the prevalence of TP53 mutations was significantly different between high- and low-risk groups; the TP53 mutations and the high TMB were both associated with a worse prognosis in patients with HCC. We also observed widely associations between risk signature and drugs sensitivity in HCC.A novel EMT-related lncRNAs risk signature, including 12 lncRNAs, was established and identified in patients with HCC, which can accurately predict the prognosis of HCC patients and may be used to guide individualized treatment in the clinical practice. Hepatocellular carcinoma (HCC) is one of the most common aggressive tumors that ranks as the fourth leading cause of cancer-related mortality worldwide . DespiteEpithelial-mesenchymal transition (EMT) is a process that leads to cell morphology and function changes, which is characterized by the dissolution of cell-cell junctions, synthesis of extracellular matrix, increasing cell motility that consequently result in the cells gaining invasive and metastatic properties , 5. NumeLong non-coding RNAs (lncRNAs), which account for 80–90% of all ncRNAs, structurally contain more than 200 nucleotides. It has been wildly applied in early diagnosis and prognosis biomarkers of various tumors , 12. AccTherefore, the objective of this study was to construct and validate an EMT-related lncRNAs signature to determine the prognosis and drugs response of patients with HCC, we first constructed and identified an EMT-related lncRNAs prognostic model based on the data extracted from The Cancer Genome Atlas (TCGA) and then explored the association of the risk model with biological functions, immune cells infiltration, somatic mutations, and sensitivity of clinical drugs, in the patients with HCC. The flowchart of this study was shown in n = 362), and the corresponding clinical data  were downloaded from the TCGA database.1 The genes were annotated and sorted as 19,659 protein-coding genes and 14,142 lncRNAs according to the ENSEMBL database.2 The exclusion criteria of this study were set as follows: (1) Samples without intact genomics for analysis; (2) The genes with an average value <1; (3) The patients whose clinical follow-up time less than 30 days. The remaining data of 343 HCC samples with 710 lncRNAs and 11,282 protein-coding genes were included in our study. The patients were stochastically assigned into the training (n = 240) and testing group (n = 103) at the rate of 7:3 using “caret” package of R v.4.0.4 software3 (The RNA sequencing (RNA-Seq) data in FPKM (fragments per kilobase of transcript per million mapped reads) format of HCC project , single nucleotide polymorphism (SNP) data .p < 0.05. Then, we incorporated these lncRNAs into the least absolute shrinkage and selection operator (LASSO) and multivariate Cox regression to construct a prognostic signature for HCC patients. Eventually, 12 lncRNAs were enrolled into the risk model. According to the multivariate Cox regression coefficient and expression value of each lncRNA, the risk score of each patient was calculated using following equation:To estimate the prognostic value of EMT-related lncRNAs, we applied multiple analyses to build the prognostic risk signature in the training group. First, we performed univariate Cox regression and Kaplan-Meier survival analysis to identify the survival associated lncRNAs, the significant lncRNAs were defined as p < 0.05 was considered to be statistically significant.where coef represents the regression coefficient and βis the expressive value of each EMT related lncRNA. The HCC patients in the training cohort were divided into high- or low-risk groups based on the median risk score. Similarly, the patients in testing and entire cohorts were allocated to either high-risk or low-risk groups. Thereafter, we conducted the Kaplan-Meier survival analysis to compare the overall survival (OS) between the high- and low-risk groups. Time-dependent receiver operating characteristic (time-ROC) curves were sketched to evaluate the predictive accuracy of the risk signature for 1-, 3-, and 5-year survival via “survivalROC” R package. Meanwhile, the stratification analyses were performed in entire cohort to assess the prognostic value of the risk signature in different populations, which based on the following clinicopathological features: age (≤65 and >65 years), gender , grade (Grade 1–2 and Grade 3–4), and clinical stage (Stage I–II and Stage III–IV); p < 0.05 was considered to be statistically significant. A multi-indicator receiver operating characteristic (multi-ROC) curves were drawn and the area under the curve (AUC) were calculated to compare the predictive ability between the risk signature and other clinicopathological features.Thereafter, Cox proportional-hazards analyses were performed to determine the independent factors for the prognosis of HCC patients, including the following clinicopathological factors: age, gender, grade, clinical stage, and risk signature; 5 and “ggalluvial” R package were employed to visualize the co-expression correlation.Additionally, the relevancy between the 12 prognostic EMT-related lncRNAs and EMT-related protein-coding genes was analyzed by using above Pearson correlation coefficient analysis and presented with co-expression network. The Cytoscape 3.8.2 softwareBased on the risk score and conventional clinical characteristics , we established a nomogram in training, testing, and entire cohort to quantitatively assess the 1- and 3-year survival probability of HCC patients using the “survival” and “rms” R packages. Moreover, we assessed the predictive performance of the nomogram with calibration curves and ROC curves using “rms” and “foreign” packages of R.6 Based on the risk signature, 343 samples were divided into high- and low-risk groups, the enriched pathways were identified by GSEA analysis and Gene Ontology (GO) analysis in the two risk groups. In GSEA analysis, the c2.cp.kegg.v7.4.symbols.gmt downloaded from MSigDB7 was used as the reference and a false discovery rate (FDR) of q-value <0.05 was used to identify the significantly enriched pathways. The significant cancer-related pathways were presented in the result. Thereafter, differential expressed genes (DEGs) were extracted from TCGA database depending on the risk grouping and the statistical significance was defined as FDR < 0.05 and | log2FC| ≥ 1. According to the DEGs, GO analysis was conducted to evaluate the related biological pathways in the two risk subgroups. Corrected p-values <0.05 were considered significant, and the top 10 most significant biological pathways were displayed with bar charts and bubble plots.The transcriptome data of the entire group were selected for gene set enrichment analysis (GSEA) using the GSEA v.4.1.0 software.p < 0.05 was considered as statistical significance.According to the EMT-related lncRNAs prognostic model, single-sample gene set enrichment analysis (ssGSEA) was conducted to explore the correlation between the risk signature and immune cells infiltrating and the immune-related pathways. First, 16 immune infiltration cells and 13 immune-related pathways scores were calculated in each LIHC sample based on ssGSEA method using “GSVA,” “limma,” and “GSEABase” R package. Then, we compared the difference of immune cells infiltration and immune-related pathways in different risk groups. The result was visualized with boxplot using the “ggpubr” R package, and 8 Then, we integrated the SNPs data and risk grouping, and explored the correlation between SNPs and risk signature. The top 20 driver genes with highest mutational frequencies and its mutation types in the high-risk and low-risk groups were displayed with waterfall plots using “GenVisR” R package. Next, chi-square test was performed to compared the gene mutational frequency between two risk groups. Kaplan–Meier survival analysis was applied to evaluate the prognostic role of TP53 mutation status, TMB, as well as TMB combined with risk signature in patients with HCC via “survival” package of R. p < 0.05 indicated a statistical significance.The format (MAF) files of HCC SNPs mutation dataset, possessed by the method of “varscan,” were obtained from TCGA database. The genes mutation status, variant classification, and the tumor mutation burden (TMB) of each patient were acquired using the Perl 5.30.0 software.p-value <0.05 was considered as significant difference.To investigate the role of EMT-related lncRNAs risk signature in predicting the sensitivity of chemotherapy and targeted therapy of HCC patients, we applied the pRRophetic algorithm to calculate the drugs half-maximal inhibitory concentration (IC50) based on the Cancer Cell Line Encyclopedia (CCLE) by using “pRRophetic” R package . Accordi9p-value <0.05 was deeded statistically significant.It was reported that the immune checkpoint related genes can effectively reflect the response rate of immune checkpoint inhibitors (ICIs), and immunophenoscore (IPS) associated with the responds to ICIs , 30. Thu2 in a humidified incubator.Human HCC cell lines  were purchased from the Cell Bank of Typical Culture Preservation Committee of Chinese Academy of Sciences . The other three HCC cell lines  and one normal liver cell line (L-02) were purchased from Procell Life Science and Technology Co., Ltd. . Cells were cultured in high glucose Dulbecco’s modified Eagle medium (DMEM) with 10% FBS , 100 μg/mL streptomycin and 100 U/mL penicillin sodium . The cells were incubated at 37°C with 5% CO® Premix Ex Taq™ II  on a CFX96 Real-Time PCR Detection System. The reaction conditions were 94.0°C for 30 s, followed by 94.0°C for 4 s, 58.0°C for 15 s, and 72°C for 15 s, for a total of 40 cycles. Relative mRNA expression of HCC cells was calculated by the 2–ΔΔCt method, while 2–ΔCT was used to reckon the mRNA expression in HCC tissues, and the data was normalized by the endogenous control of Glyceraldehyde 3-phosphate dehydrogenase (GAPDH). qPCR assays were performed in triplicates. The lncRNA Primers were listed in Total RNA was isolated from HCC cells and tissue samples using Trizol Reagent  according to the product manual. Subsequently, the RNA was reversely transcribed to complementary DNA (cDNA) using the PrimeScript™ RT reagent kit with gDNA Eraser  according to the product instructions. The qPCR was conducted with TB Green10 Perl 5.30.0 software (see text footnote 8) and GraphPad Prism 8.0 software.11 Chi-square test was used to analyze the baseline characteristics of patients with HCC. Student’s t-test or Wilcoxon rank-sum test was applied to compare differences between the two groups. LASSO and Cox regression analyses were used to build a prognostic model. Kaplan-Meier analysis with log-rank test was used to evaluate the survival differences of the two groups. The ROC curve was used to estimate the predictive ability of the risk models. The predictive values of the nomogram for 1- and 3-year OS were assessed using calibration and ROC curves. All statistical tests were two-sided and p < 0.05 was considered statistically significant.Statistical analyses were performed using the R software v.4.0.4,p < 0.001.A total of 424 HCC samples with transcriptome data  and 377 HCC specimens containing clinical information were acquired from TCGA database. After removing the repeated samples, and patients with incomplete clinicopathological data and less than 30 days follow-up time, the remaining 343 patients with complete follow-up information and 319 patients with complete clinicopathological data were included in this study for subsequent analysis. Of the 343 samples, 240 patients were randomly assigned to the training set, 103 patients were distributed to testing set. The clinicopathological features of the HCC patients included in this study are shown in We identified 449 EMT-related lncRNAs in above analysis, of which 41 were significantly correlated with the survival of HCC patients based on univariate Cox regression analysis and Kaplan-Meier analysis in the training set . Thereafn = 120) and high-risk subgroup (n = 120) basing on the median risk score . Kaplan-Meier survival curve indicated that the HCC patients in the high-risk group had worse OS than those in the low-risk group (p = 5.304e-06), as shown in Based on the expression value of each lncRNA and corresponding regression coefficient, the individualized risk score was calculated as the following formula: Risk score = (–0.124 × AC103760.1 expression) + (–0.113 × AC015908.3 expression) + (–0.027 × LINC02362 expression) + (–0.021 × LINC02499 expression) + (–0.009 × F11.AS1 expression) + (0.02 × LINC00942 expression) + (0.03 × PRRT3.AS1 expression) + (0.033 × AC012146.1 expression) + (0.122 × AC092171.2 expression) + (0.142 × AC099850.3 expression) + (0.163 × CASC19 expression) + (0.313 × AL158206.1 expression). HCC patients in the training set were divided into low-risk subgroup , p < 0.001] were independent predictors for OS in patients with HCC , with HCC . Moreovewith HCC , which dp = 1.87e-02, p = 2.972e-06, To evaluate the applicability of the risk model, we conducted Kaplan-Meier analysis and Cox proportional hazards regression analysis in the testing and the entire cohorts. Firstly, we calculated the risk score of HCC patients in the validation cohorts according to the above-mentioned formula. The median risk score in the training cohort was applied to divide the patients  into low-risk group or high-risk group. Kaplan–Meier analysis of the validation groups revealed that HCC patients with low risk had longer OS than those with high risk in testing set , gender , histological grade (grade 1–2 and grade 3–4), and clinical stage (stage I-II and stage III-IV). Then, Kaplan–Meier survival curve analysis was conducted in different subgroups. The results showed that patients with high risk in different age and clinical stage subgroups had worse survival than those with low risk, and the same results were observed in the male and Grade 1–2 subgroup. However, there was no significant difference in the female subgroup and patients with grade 3–4, which suggested that the prognostic signature was applicable in most subgroups of HCC .p = 0.0023) and AC092171.2 (p = 0.0196) were significantly highly expressed in HCC tissues; whereas, no significant difference was observed in AL158206.1, and CASC19 between tumor tissues and para-carcinoma tissues  with the greatest influence on the survival, which had confirmed in Cox proportional hazards regression analysis , were se tissues . These r tissues .We incorporated age, gender, grade, clinical stage, and risk score to establish a nomogram both in training cohort and validation cohorts to predict the 1- and 3-year OS for patients with HCC. The Comprehensive scores were obtained by combining each clinical factor; the higher the total score of patients, the worse the prognosis . The preNext, we compared the predictive performance of the risk signature built in this study with other five EMT-related prognostic models for HCC, including the EMT-related five-lncRNA signature , EMT-relq-value) < 0.05, as shown in Gene set enrichment analysis was conducted in the entire group to probe the potential biological mechanism of the EMT-related lncRNAs signature. The results suggested tumor-related pathways, including bladder cancer, thyroid cancer, pathways in cancer, VEGF signaling pathway, cell cycle, and DNA replication were highly enriched in the high-risk group with FDR (p < 0.05) were identified in the high-risk group compared to the low-risk group. We then selected the DEGs for GO enrichment analysis, and the results showed that these DEGs were mainly enriched in terms associated with cell division process   cells were upregulated in the low-risk group ( < 0.05) . These fp < 0.001) (p = 0.0163), indicating that the HCC patients with TP53 mutation had worse prognosis than those without TP53 mutation (p < 0.001) (It has been confirmed that SNPs contributes to tumorigenesis and tumor progression. Tumor mutation burden (TMB) is defined as the total number of somatic mutations detected per million bases, including gene coding errors, base substitution, gene insertion or deletion errors. TMB has been reported to be used as a valid prognostic biomarkers and immune therapy response indicators in many kinds of tumor . Thus, w< 0.001) . A signimutation . Meanwhi< 0.001) . The pat< 0.001) . CollectTo explore the different response to drugs treatment between high- and low-risk groups, we applied the pRRophetic algorithm to estimate the IC50 of chemotherapeutic agents and targeted drugs, and compared the IC50 of different drugs in two risk groups with Wilcoxon rank-sum test. Doxorubicin, camptothecin, mitomycin C, cisplatin, gemcitabine, and sorafenib were included in this analysis. As shown in P < 0.05)  . Among t < 0.05) . This re < 0.05) . The resHepatocellular carcinoma is one of the most common malignant tumors worldwide, characterized by high recurrence rates, high mortality rates, and poor prognosis in patients . GrowingPrevious researches have revealed that lncRNAs participate in the regulation of EMT and ultimately affect tumor progression and metastasis. Moreover, EMT-related lncRNAs could serve as novel and effective biomarkers and therapeutic targets for various tumors . HoweverSome lncRANs in this risk model have been reported to be associated with the malignant phenotypes of HCC or other cancers. For instance, LINC02499 was significantly downregulated in HCC tissues compared to para-cancerous tissues, and its low expression was also remarkably correlated with poorer overall survival . lncRNA Epithelial–mesenchymal transition promote tumor progression and metastasis not only through reprogramming of cancer cells but also through reshaping tumor microenvironment (TME) . NumerouIncreasing evidence has demonstrated that EMT is also involved in other malignant behaviors, such as irradiation resistance, chemoresistance, and targeted drug resistance in HCC , 52–55. There are a few limitations in this study. First, the 12 EMT-related lncRNAs risk signature was constructed and evaluated using limited data and clinical information from TCGA database, but without external validation from other database or clinical samples, which may limit the generalizability of our model. In addition, some of the lncRNAs reported in this study have not been previously studied; therefore, it is critical to verify the functional features and molecular mechanisms of the risk signature model. Next, we will continue to pay attention to the role of the signature in clinical practice and further conduct related experiments to explore the functions and mechanisms of the EMT-related lncRNAs. Besides, in recent years, single-cell multi-omics approaches and spatial transcriptomics are becoming available and wildly applied in discovering distinctive biomarkers and exploring tissue cytoarchitectures and functions , 57. ThuIn conclusion, our study established a novel EMT-related prognostic risk signature including 12 lncRNAs and constructed a nomogram to predict the overall survival of HCC patients, which may improve the prognostic predictive efficacy and guide the individualized treatment for the patients with HCC.The datasets presented in this study can be found in online repositories. The names of the repository/repositories and accession numbers can be found in the article/The studies involving human participants were reviewed and approved by the Second Affiliated Hospital of Nanchang University Medical Research Ethics Committee. The patients/participants provided their written informed consent to participate in this study.SH and JW: conceptualization. SH: investigation. LZ, DL, and JZ: methodology. LZ and DL: supervision. LZ and JZ: visualization. SH: writing-original draft. JW: writing-review and editing. All authors have read and agreed to the published version of the manuscript.The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.


Bacillus velezensis significantly inhibited the growth of the grape postharvest pathogen Penicillium olsonii.Pathogen infection influences the post-harvest shelf life of grape berries. In a preliminary study, metabolites produced by B. velezensis and P. olsonii, a draft genome was generated for P. olsonii WHG5 using the Illumina NovaSeq platform, and the transcriptomic changes in WHG5 were analyzed in response to the exposure to B. velezensis metabolites (10% v/v).To investigate the mechanism of interaction between GCY1, brlA, and abaA, were down-regulated compared with those of the control. In addition, spore deformation and abnormal swelling of the conidiophore were observed. The expression of crucial enzymes, including fructose 2,6-bisphosphate and mannitol-2-dehydrogenase, was down-regulated, indicating that the glycolytic pathway of WHG5 was adversely affected by B. velezensis metabolites. The KEGG pathway enrichment analysis revealed that glutathione metabolism and the antioxidant enzyme system were involved in the response to B. velezensis metabolites. The down-regulation of the pathogenesis-related genes, PG1 and POT1, suggested that B. velezensis metabolites decreased the pathogenicity of P. olsonii. B. velezensis metabolites disrupted the homeostasis of reactive oxygen species in P. olsonii by affecting glucose metabolism, resulting in spore deformation and disruption of growth. In addition, the expression of key pathogenesis-related genes was down-regulated, thereby reducing the pathogenicity of P. olsonii.The expression levels of genes associated with sporulation, including P. olsonii to B. velezensis metabolites and identifies potential target genes that may be useful in biocontrol strategies for the suppression of post-harvest spoilage in grapes.This study provides insights into the responses of  Vitis vinifera L.) are among the most popular fresh fruit worldwide and have a relatively long post-harvest shelf life. However, pathogen infection strongly influences the post-harvest shelf life of grape berries  and their metabolites . Biologisistance .Bacillus strains are the most prominent bioactive compounds for plant protection  against Rhizoctonia solani but not in grapevine  examine the response of P. olsonii to metabolites produced by B. velezensis, (2) generate a draft genome for P. olsonii WHG5 as a tool for further genetic analysis, and (3) elucidate the mechanisms of B. velezensis antifungal activity on P. olsonii. The results provide insight into the potential of metabolites produced by B. velezensis for effective biocontrol of post-harvest fruit rot to enhance the storage longevity of grape berries.Our previous study provided the first report of the fungal pathogen f grapes . In a prPenicillium olsonii WHG5 was isolated from rotting berries of grape (V. vinifera “Crimson”) using the single spore isolation technique developed by B. velezensis isolate SB023 was obtained from the China General Microbiological Culture Collection Center, Beijing, China. An SB023 cell suspension was generated by culturing a single colony for 48 h at 32°C with shaking at 200 rpm in nutrient broth . All cell suspensions were mixed with 50% (v/v) glycerin solution  and stored at −80°C.8 CFU/ml as measured with a hemocytometer. An aliquot (1 ml) of the cell suspension was inoculated into 100 ml NB, incubated under the same conditions, and then the culture was centrifuged at 10,000 g for 15 min. The cell-free supernatant was filtered through a Millex-HV filter  to obtain the sterile B. velezensis liquid-culture metabolites.A sample (100 μl) of the preserved SB023 cell suspension was activated in 10 ml NB by incubation for 48 h at 32°C with shaking at 200 rpm and then adjusted to approximately 1 × 108 CFU/ml, as measured with a hemocytometer. An aliquot (1 ml) of the culture was added to 100 ml PDB supplemented with 10% (v/v) B. velezensis metabolites. An identical volume of PDB supplemented with the equivalent volume of sterile distilled water served as the control. All liquid cultures were incubated for 5 days at 28°C with shaking at 200 rpm and then were used for DNA and RNA extraction. All experiments were repeated three times with three replicates.The WHG5 cell suspension was activated in 10 ml potato dextrose broth  by incubation for 24 h at 28°C with shaking at 200 rpm, and then adjusted to approximately 1 × 10de novo assembled with A5-miseq v20150522  in accordance with the manufacturer’s instructions. Strains were sequenced and the reads were assembled  using the following procedure. The genomic DNA was sheared using a g-TUBE . A library of 400-bp paired-end reads was constructed in accordance with the standard Illumina TruSeq DNA sample preparation guide and sequenced using the Illumina NovaSeq platform  with a read length of 150 bp. The FastQC tool  was used20150522  and SPAd20150522 . The gen20150522 , and the20150522 . Ultimatde novo prediction of genetic models in the WHG5 genome  and BLASTP (v2.5.0+) tools were used to predict the presence of CAZy enzyme and cytochrome P450 genes in the genome sequence, respectively . Predictsoftware . Finallysoftware .Total RNA was extracted using a fungal RNA kit  following the manufacturer’s instructions. The concentration and purity of the RNA were determined using a NanoDrop 2000 spectrophotometer  and an Agilent 2100 Bioanalyzer , respectively. The cDNA libraries with an average insert size of 380 bp were prepared using the Illumina mRNA-seq sample preparation kit following the manufacturer’s instructions and evaluated with an Agilent 2100 Bioanalyzer. The cDNA libraries were sequenced and analyzed  in accordance with the Illumina standard protocol. The RNA-sequencing (RNA-seq) reads were aligned to the WHG5 genome sequence assembled in this research.2 fold change > 1 and statistical significance  were used as the criteria to identify the DEGs.All read alignment positions of each paired-end read were mapped against the genome sequence and exon splicing junctions using HISAT2 software with the BWT algorithm . Read coP-value after correction) ≤ 0.05 were defined as significantly enriched DEG GO terms. This analysis determined the main biological functions of the DEGs (A gene ontology (GO) enrichment analysis was performed using the topGO Bioconductor package. All DEGs were mapped to corresponding GO terms and the number of genes in each term was calculated. The GO terms with significant enrichment of DEGs compared with the genomic background were defined using the hypergeometric test. The GO terms with a false discovery rate of  pathway enrichment analysis was performed using the KEGG database.P. olsonii β-actin (POLN_004133) gene was used as the internal control gene for each amplification. All primers used are listed in ® Premix Ex Taq™ (Takara), and 3 μl of RNase-free water. The PCR protocol was as follows: initial denaturation at 96°C for 1 min, followed by 40 cycles at 96°C for 15 s, and primer extension at 62°C for 25 s. The relative expression level of each targeted gene was calculated using the 2–△△Ct method. Three replicates of each qRT-PCR analysis were performed for each gene.To validate the RNA-seq results, samples from the same treatment and RNA extraction for RNA-seq were also used for cDNA synthesis. The RNA was reverse-transcribed into cDNA using the PrimeScript RT Reagent Kit with gDNA Eraser . A total of 20 DEGs that differed in their expression pattern were verified by quantitative real-time PCR (qRT-PCR). The selected DEGs were mostly associated with sugar metabolism, alternative carbon metabolism, glutathione metabolism, and plant–pathogen interactions. Primers for the selected DEGs were designed using Primer Premier v5.0 . The B. velezensis metabolites or the equivalent volume of sterile distilled water (the control) and cultured at 28°C for 72 h. The micromorphology of P. olsonii conidia and mycelia was observed with a light microscope .Plates containing PDA medium were inoculated with 100 μl of WHG5 cell suspension and incubated at 28°C for 24 h. A small plug of the culture (diameter 5 mm) was inoculated onto plates containing PDA supplemented with either 10% Reduced glutathione was quantified in accordance with the spectrophotometric assay method of t-tests at the 5% significance level (P < 0.05).To ensure the validity of the experimental data and to reduce the variance, all tests were performed in triplicate. All statistical analyses were performed with GraphPad Prism v7.0 . The significance of differences between the means of the treatments was analyzed with one-way ANOVA followed by paired-sample P. olsonii WHG5 ; amino acid transport and metabolism ; and post-translational modification, protein turnover, and chaperones . In addition, carbohydrate-active enzymes (CAZymes) were important in the P. olsonii WHG5 genome , 135 and 259 DEGs were up-regulated and down-regulated, respectively, in WHG5 cultured with B. velezensis metabolites , a crucial enzyme in the interconversion of mannitol and fructose, was down-regulated in the treatment group. Genes encoding alpha-amylase A  and glucoamylase  showed the same pattern. AMY1 is essential for the synthesis of a virulence factor and hence is associated with virulence. In addition, DEGs encoding other crucial enzymes were up-regulated in the treatment group, including 6-phosphate-N-acetylglucosamine deacetylation , 6-phosphate glucosamine deaminase , and hexokinase , which are key enzymes involved in the breakdown of fructose and other sugars into fructose-6-phosphate for glycolysis. It was notable that the up-regulated enzymes also included trehalose 6-phosphate synthase , which is a critical enzyme in trehalose synthesis. In addition, the trehalose content was significantly increased (P < 0.05) in the treatment group  involved in β-oxidation of fatty acids, glutaryl-CoA dehydrogenase  involved in glutamate metabolism, glycerol 2-dehydrogenase  and glyceraldehyde-3-phosphate dehydrogenase  involved in glycerol metabolism, and cytochrome b2  involved in lactate metabolism were down-regulated in the treatment group. Conversely, key genes in other sources of acetyl-CoA were up-regulated in the treatment group, including DEGs encoding alcohol dehydrogenase  involved in ethanol metabolism, and acetyl-CoA synthetase  and related acetyltransferases  involved in acetate metabolism. These results implied that B. velezensis metabolites influenced the β-oxidation of fatty acids, glutamate metabolism, glycerol metabolism, and lactate metabolism, and increased the metabolism of ethanol and acetate in P. olsonii. In the glyoxylate cycle, isocitrate is converted to malate through the glyoxylate process and utilizes acetyl-CoA. It is worth mentioning that two DEGs encoding key proteins in this process, succinyl-CoA (POLN_006914) and 2-oxoglutarate-malate carrier , were down-regulated in the treatment group, which indicated that isocitrate conversion to malate through the succinate process was decreased by B. velezensis metabolites.As an important metabolic adaptation strategy, alternative carbon metabolism is utilized by a fungus to compensate for the deficiency of the preferred carbon source, glucose. In such a harsh microenvironment, the fungus converts other carbon sources to the central metabolite acetyl-CoA to fuel the glyoxylate cycle and gluconeogenesis for glucose and energy production. After exposure of tabolism . DiffereB. velezensis metabolites affected GSH metabolism in P. olsonii  were identified in the treatment group, of which one (POLN_004024) was up-regulated. As the main source of GSH, glutamate synthesis was affected in the treatment group by the down-regulation of the genes encoding glutamate dehydrogenase  and amino-acid acetyltransferase . GDH converts glutamate into glutamine, whereas argJ converts glutamate into ornithine and participates in the citrate cycle. Two DEGs encoding enzymes that participate in the interconversion of GSH and GSSH, namely 6-phosphogluconate dehydrogenase  and glutathione transporter , were up-regulated in the treatment group, indicating that interconversion between GSH and GSSH in P. olsonii was activated in response to exposure to B. velezensis metabolites. A gene encoding thioredoxin reductase  was down-regulated in the treatment group, indicating that thioredoxin metabolism was decreased. In addition, the glutathione content was increased and intracellular ROS generation was reduced in the treatment group (P < 0.05) , and peroxidases] and non-enzymatic [glutathione (GSH)] mechanisms maintain the redox homeostasis within the cells. In these processes, the oxidation status is maintained and rapidly restored by the action of two redox-balancing systems: the GSH and thioredoxin pathways. In the present study, DEGs were enriched in the GSH pathway, indicating that  olsonii . Four DE < 0.05) . HoweverP. olsonii on PDA plates supplemented with B. velezensis metabolites , stearoyl-coenzyme A desaturase 1 , and phosphate-repressible acid phosphatase  were down-regulated in the treatment group. PG1 is a key virulence protein of post-harvest pathogens, OLE1 is associated with fungal virulence, and PHOA is one of the main toxins of Penicillium species. Thus, B. velezensis metabolites may affect the pathogenicity of P. olsonii. In addition, given that spore formation requires the participation of mannitol, genes associated with sporulation were down-regulated in the treatment group, including GCY1 and AMY3 mentioned in relation to carbon metabolism, PFK, and brlA , a gene associated with conidia formation. These results indicated that B. velezensis metabolites may alter the normal sporulation of P. olsonii. To verify these results, the development of P. olsonii spores and mycelia was observed microscopically. The conidial spores were deformed and the swelling of the mycelia of P. olsonii was observed after exposure to B. velezensis metabolites  that generate fructose-6-phosphate, a central metabolite in sugar metabolism. This finding is consistent with previous research on fungi under stress  of A. alternata and A. brassicicola, which are deficient in mannitol synthesis, show greatly reduced virulence in tobacco and cabbage, respectively  involved in alternative carbon metabolism, including ethanol metabolism and acetate metabolism   . Hence, P. olsonii caused by B. velezensis metabolites. In addition, multiple genes associated with the glutathione cycle  were differentially expressed in P. olsonii in response to exposure to B. velezensis metabolites. These changes were indicative of the damage to P. olsonii caused by B. velezensis metabolites and the compensatory responses of P. olsonii to this adverse stress. Treatment with B. velezensis metabolites decreased the expression levels of genes encoding GST, TRR, GDH, argJ, and SOD, and increased the content of reduced glutathione, which restricted the reduction and utilization of glutathione and the scavenging of free radicals, and thus may have disrupted the redox homeostasis in P. olsonii. P. olsonii responded to the stress caused by B. velezensis metabolites by up-regulating the expression of genes encoding PDG and fructose-bisphosphate aldolase, which are important enzymes in the pentose phosphate pathway  was down-regulated in P. olsonii after exposure to B. velezensis metabolites. PHOA is the primary toxin among the group of secondary metabolites formed by the fungus (PHOA in P. olsonii caused by B. velezensis metabolites is an additional indication of the potential of B. velezensis metabolites as an eco-compatible alternative to harmful chemical fungicides.Several genes involved in plant–pathogen interactions were down-regulated in nfection . In partnfection . Down-ree fungus . TherefoBacillus velezensis metabolites inhibit mycelial growth and cause the deformation of the conidia of the grape post-harvest pathogen P. olsonii WHG5. Genomic and transcriptomic analyses indicate that B. velezensis metabolites affect the expression of genes that influence the mycelial growth of P. olsonii. The inhibition of mycelial growth might be due to an initial impact on normal sugar metabolism and subsequent disturbance of alternative carbon metabolism and the stimulation of glutathione metabolism to maintain redox homeostasis. Although P. olsonii was grown on a PDA medium in this study, genes involved in plant–pathogen interactions were down-regulated by B. velezensis metabolites, which further verified the effect on the pathogenicity of P. olsonii. The results provide an overview of the main responses of P. olsonii to B. velezensis metabolites and highlight potential target genes for biocontrol agents to suppress post-harvest spoilage in grapes.SRX17100770 and SRX17100771.The data presented in this study are deposited in the NCBI SRA repository, accession numbers TZ performed the experiments and wrote the original draft of the manuscript with the assistance of GW and SJ. BS and ZC carried out data curation and participated in the revision of the manuscript. SJ designed the research and provided financial support. All authors have read and approved the submitted version of the article.


To evaluate the difference between multiple primary lung adenocarcinoma (MPLA) and solitary primary lung adenocarcinoma (SPLA) by delta-radiomics based machine learning algorithms in CT images.A total of 1094 patients containing 268 MPLAs and 826 SPLAs were recruited for this retrospective study between 2014 to 2020. After the segmentation of volume of interest, the radiomic features were automatically calculated. The patients were categorized into the training set and testing set by a random proportion of 7:3. After feature selection, the relevant classifiers were constructed by the machine learning algorithms of Bayes, forest, k-nearest neighbor, logistic regression, support vector machine, and decision tree. The relative standard deviation (RSD) was calculated and the classification model with minimal RSD was chosen for delta-radiomics analysis to explore the variation of tumor during follow-up surveillance in the cohort of 225 MPLAs and 320 SPLAs. According to the different follow-up duration, it was divided into group A (3–12 months), group B (13–24 months), and group C (25–48 months). Then the corresponding delta-radiomics classifiers were developed to predict MPLAs. The area under the receiver operator characteristic curve (AUC) with 95% confidence interval (CI) was quantified to evaluate the efficiency of the model.To radiomics analysis, the forest classifier (FC-radio) with the minimal RSD showed the better stability with AUCs of 0.840  and 0.670  in the training and testing set. The AUCs of the forest classifier based on delta-radiomics (FC-delta) were higher than those of FC-radio. In addition, with the extension of follow-up duration, the performance of FC-delta in Group C were the best with AUCs of 0.998  in the training set and 0.853  in the testing set.The machine-learning approach based on radiomics and delta-radiomics helped to differentiate SPLAs from MPLAs. The FC-delta with a longer follow-up duration could better distinguish between SPLAs and MPLAs.The online version contains supplementary material available at 10.1186/s12885-022-10036-1. Lung carcinoma is the commonest cause of cancer-related death in China and is also a major health challenge worldwide . The freAdenocarcinoma has become the most prevalent sub-type of lung cancer. Therefore Evaluating the multiple primary lung adenocarcinomas (MPLAs) from solitary primary lung adenocarcinomas (SPLAs) by radiological methods is of great significance, while the conventional experience was difficulty in diagnosis . FurtherThis retrospective study was approved by the Institutional Review Board of Zhejiang Provinical People’s Hospital (NO. 2020QT108), which waived the informed consent of all patients.nd edition of ACCP evidence-based clinical practice guidelines [This retrospective study enrolled 1094 patients who were pathologically diagnosed as lung adenocarcinoma after 6 years follow-up surveillance, including 826 patients with SPLAs and 268 MPLAs, from January 2014 to December 2020. Among these patients, there were 320 SPLAs and 225 MPLAs patients with regular surveillance were incorporated for delta-radiomics analysis . The scan parameters were as follows: tube voltage, 120 kVp; tube current, 200 mA; rotation speed, 0.75 s; beam pitch, 1.375; pixel matrix, 512*512; detector collimation, 64*0.625 mm; slice thickness, 2.0 mm; reconstruction interval, 2.0 mm; width of lung window, 1500HU; level of lung window, -600HU.http://www.itksnap.org/pmwiki/) by two radiologists with 10 (Doctor Ma) and 12 years (Doctor Li) of experience, manually  was depicted in software of “ITK-snap 3.8.0”  was carried out . After tWith consideration of the different progression during regular follow-up surveillance between MPLAs and SPLAs, the delta-radiomics was utilized. The delta-radiomics was defined as the change of radiomic features between baseline and follow-up surveillance, which was divided into three groups including Group A (3–12 months), Group B (13–24 months), and Group C (25–48 months), according to different follow-up surveillance. The equation of delta-radiomics was: (follow-up radiomics—baseline radiomics)/follow-up interval. The specific information of radiomics and delta-radiomics analysis were listed in p-value less than 0.05 indicates statistical significance.The general clinical characteristics were analysis by software of “SPSS 22.0” with methods of student’s t-test or chi-square test. The methods of radiomic feature selection including variance, correlation analysis, GBDT, and machine learning algorithms were performed by the software of “Python 3.5”. The ROC curve was delineated by the software of “MedCalc 15.8”. A p = 0.279) and age (p = 0.575) had no statistical significance, while the variables of location (p < 0.05) and pathology (p < 0.05) showed the significant difference. The tumors of SPLAs were more likely to locate in the right lung than MPLAs (62.2% vs. 60.1%). The pathological type of MPLAs was easier to be MIA (45.9% vs. 32.7%), while that of SPLAs was more prone to be IAC (67.3% vs. 54.1%).There were 1094 patients with 268 MPLAs and 826 SPLAs. The general information of all patients were listed in Table The radiomic features between the patients of MPLAs and SPLAs were analyzed. There were 27 radiomic features remained after feature selection of GBDT Fig.  and the Regardless of the poor efficiency of the FC-radio in distinguishing MPLAs and SPLAs, a further forest machine learning algorithm of delta-radiomics (FC-delta) was conducted. Depending on the different duration of follow-up, we divided the patients into three groups: group A with a follow-up intervals of 3–12 months (105 MPLAs vs. 145 SPLAs), group B with a follow-up intervals of 13–24 months (68 MPLAs vs. 96 SPLAs), and group C with a follow-up intervals of 25–48 months (52 MPLAs vs. 79 SPLAs).The AUC of FC-delta in group A was 0.972  in the training set and was 0.798  in the testing set. The AUC of FC-delta in group B was 0.989  in the training set and was 0.821  in the testing set. The AUC of FC-delta in group C was 0.998  in the training set and was 0.853  in the testing set. With the extension of follow-up intervals, the difference between MPLAs and SPLAs was more obvious . This result supported the previous view that the proportion of MIA and adenocarcinoma in situ is high in synchronous multiple primary lung carcinomas [We reported a single-institution experience on radiomic differentiation on MPLAs from SPLAs, especially emphasis on their long-term variation. The reported incidence of synchronous lung carcinoma is variably between 0.2 to 20% . In our rcinomas . This alrcinomas . HoweverWe used the method of manual segmentation to delineate tumoral VOI for radiomic analysis. Comparing with automatic and semi-automatic segmentation, manual segmentation carried a certain amount of subjectivity. Therefore the radiomic features greater than 0.75 were selected as robust features and the their mean values from two radiologists were taken for further analysis. It has been reported that radiomics features with a high ICC for volunteer can be considered candidates for radiomics studies . Though The crucial challenge regarding MPLAs is what they differed with SPLAs in the course of development, on which both the treatment strategies and prognosis are based . The posnd edition of ACCP in our research. Second, the MPLAs can be subdivided into synchronous and metachronous phenotypes. Due to the limitation of incidence and sample size, we performed a general analysis of MPLAs which may lead to a biased result. Third, we only enrolled the cohort with pathological types of MIA and IAC to analysis and neglected other pathological types of lung carcinomas. The multiple and solitary primary lung carcinomas with pathological types of adenocarcinoma in situ, squamous carcinoma [Our present study has several limitations. Currently, there are no definitive guideline for the diagnosis and treatment of MPLAs. In 2003, the American College of Chest Physicians (ACCP) developed a new diagnostic criteria for multiple primary lung carcinomas with evaluations of lymphatic and systemic metastasis and the interval between metachronous multiple primary lung carcinomas was extended to at least 4 years . Antakliarcinoma , and so In conclusion, our study revealed that the approaches of radiomics and delta-radiomics help to differentiate MPLAs and SPLAs. The radiomic difference between SPLAs and MPLAs was faint and the delta-radiomics better differentiate these patients. Moreover, with the extension of follow-up duration, the delta-radiomics difference between SPLAs and MPLAs appeared more distinctly.Additional file 1.


In the cocktail party situation, people with normal hearing usually follow a single speaker among multiple concurrent ones. However, there is no agreement in the literature as to whether the background is segregated into multiple streams/speakers. The current study varied the number of concurrent speech streams and investigated target detection and memory for the contents of a target stream as well as the processing of distractors. A male-voiced target stream was either presented alone (single-speech), together with one male-voiced distractor (one-distractor), or a male- and a female-voiced distractor (two-distractor). Behavioral measures of target detection and content tracking performance as well as target- and distractor detection related event-related brain potentials (ERPs) were assessed. We found that the N2 amplitude decreased whereas the P3 amplitude increased from the single-speech to the concurrent speech streams conditions. Importantly, the behavioral effect of distractors differed between the conditions with one vs. two distractor speech streams and the non-zero voltages in the N2 time window for distractor numerals and in the P3 time window for syntactic violations appearing in the non-target speech stream significantly differed between the one- and two-distractor conditions for the same  speaker. These results support the notion that the two background speech streams are segregated, as they show that distractors and syntactic violations appearing in the non-target streams are processed even when two speech non-target speech streams are delivered together with the target stream. In everyday environments, we often attend to speech in the presence of multiple other speech streams  were measured, because they allow one to study processes of target detection, attentional selection, working memory, and distraction. Target auditory events (including speech stimuli) typically elicit two successive ERP components, the N2 and the P3 . The N2bA continuous target speech stream was presented to the participants alone (single-speech condition) or in the presence of one or two continuous distractor speech stream(s): one condition with a male distractor voice (one-distractor condition) and one condition with a male and a female voice (two-distractor condition). The target stream was always delivered by a male speaker. Participants were instructed to detect numerals in the target stream by pressing a reaction key (target detection task). The distractor stream(s) also contained numerals (distractor events). Detection performance and ERPs were measured for targets together with false alarms caused and ERPs elicited by the distractor events, separately for each distractor stream . Participants were also asked to follow the target speech and to answer questions based on information presented in it (recognition task). We hypothesized that performance (both target detection and recognition performance) will be lower in the conditions with distractor speech streams compared to the single-speech condition. Concurrently, based on previous studies showing that the amplitude of the N2/P3 amplitudes to target events increase with increasing task demand , we hypoN = 29; 11 males; age: M = 21.97 years, SD = 2.04; 26 right-handed) participated in the study for modest financial compensation. None of the participants had a history of psychiatric or neurological symptoms. All participants had pure-tone thresholds of <25 dB in the 250 Hz – 4 kHz range, with <10 dB difference between the two ears. Data from two participants were excluded from the final analysis due to the loss of the EEG triggers for sound onset. Data from four participants were excluded due to extensive artifacts and bad signal-to noise ratio. Thus, data from 23 participants were analyzed . Written informed consent was obtained from all participants. The study was approved by the United Hungarian Ethical Committee for Research in Psychology (EPKEB), and it was in full compliance with the World Medical Association Helsinki Declaration and all applicable national laws.Native Hungarian speakers . Hungarian, emotionally neutral informative articles of news websites were delivered by professional actors  recorded at 48 kHz with 32-bit resolution in the same room where the experiment was conducted.All articles were reviewed by a dramaturge checking for correct syntax and natural flow of the text. The recorded speech was edited by a professional radio technician. The average RMS of the sound recordings was equalized to −32dBfs by VST-based attenuation after applying either −20 dB or −15 dB C3 compressors, depending on the dynamics of the actor reading. Audio recordings were presented by Matlab R2014a software  with Psychtoolbox 3.0.10 on two Intel Core i5 PCs with ESI Julia 24-bit 192 kHz sound cards connected to Mackie MR5 mk3 Powered Studio Monitor loudspeakers. The speech streams were presented with a fixed loudness level of ∼70 dB SPL. Speech recordings were delivered from the same position as they were recorded in order to recreate the reverberation effects of the recording situation. Thus, room acoustics effects did not differ between recording and the experimental setup. Each loudspeaker corresponded to one speaker.In three experimental conditions, one, two, or three speech streams were presented concurrently  of 2–4 syllable length. These served as targets in the target stream (targets) and distractors in the distractor stream(s). Only numerals indicating the quantity of some object within the context of the text were assigned as targets/distractors. For example, in Hungarian, the indefinite article (“egy”) is the same as the word for “one.” This word, when used as an article, did not constitute a target/distractor. There are also words, such as the Hungarian word for moonflower or daisy , which have a numeral as a component. These were not regarded as targets/distractors either. The temporal separation between successive target and distractor events was not controlled, because the articles serving as target and distractor streams were randomly paired, separately for each participant. In a representative example, the mean difference was calculated between target and distractor events: the mean difference was 2.348 s . Distractor articles (but targets not) also contained 19–26 syntactic violations , which served for control purposes, as Each article contained 45–57 numerals  0° (middle), and 30° (right) from the midline. Additionally, a 23″ monitor was placed at 195 cm in front of the participant, showing an unchanging fixation cross (“+”) during the stimulus blocks. Participants were instructed to avoid eye blinks and other muscle movements and to watch the fixation cross while listening to the speech segments. EEG was recorded during the experimental blocks.Participants performed two tasks on the target speech segments : the “nuThe stimulus blocks were presented in pseudorandomized order: in the first half of the experimental session (blocks 1–6), each condition was presented two times in random order with the restriction that no condition was immediately repeated; in the second half of the session (blocks 7–12), conditions were presented in reversed order with respect to the first half. Participants were allowed to take a break during the experiment after each stimulus block, and there was a longer mandatory break after the sixth stimulus block. Altogether, the experiment lasted ca. 4 h.Detection task performance: Button presses for correct responses (hits) were initially collected from a 0–5000 ms interval from the onset of the target event. Responses were then rejected if they were longer than 95% (>1493 ms) or shorter than 5% (<435 ms) of all of the initially collected potential target responses . From the accepted responses, log-normalized reaction times (RT) and hit rates (HR) were calculated for each participant and condition (pooling data from the four stimulus blocks of the same condition). False alarm rates (FA) were calculated by dividing the number of non-target responses  by the estimated number of non-target words in the target-stream . Detection sensitivity values d′;  were calH test, followed by Bonferroni-corrected pairwise post hoc contrasts.Recognition performance in the content-tracking task was calculated as the percentage of correct responses, separately for each participant and condition (pooling data from the four stimulus blocks of the same condition). The sensitivity of the measurement was increased by eliminating items (questions), the response to which was above 95% or below 30% correct overall (collapsed across participants and conditions). Responses with a confidence rating of “I know the answer from some other source” were also dropped from the analysis. Confidence ratings were compared between the three conditions  by the Kruskal–Wallis 2 effect size. All statistical analyses  were conducted by the STATISTICA 13.1 and JASP 0.15.0.0. software.Statistical analysis consisted of repeated-measures analyses of variance (ANOVA) with the factor of CONDITION (single-speech vs. one-distractor vs. two-distractor), separately for RT, d′, hit rate, false alarm rate, and recognition performance. Statistical analysis of distractor effect  was performed by another repeated-measures ANOVA, with the factors DISTRACTOR . The alpha level was set at 0.05. Greenhouse–Geisser correction of sphericity violations was employed where applicable and the ε correction factor is reported. All significant results are reported together with the ηEEG recording and analysis were identical to Continuous EEG data were filtered with a 0.5–80.0 Hz Kaiser bandpass-filter and a 47.0–53.0 Hz Kaiser bandstop filter  using the EEGlab 14.1.2.b toolbox . EEG datAmplitudes were measured from frontal , cental , and parietal  electrodes for statistical analysis, allowing also to compare response amplitudes across the left , midline , and right  areas. Time windows for measuring the ERP amplitudes were selected between 150 and 280 ms for N2 and between 620 and 770 ms for P3 relative to stimulus onset, both for target and non-target numerals. The average number of artifact-free target numerals were 150.17 (SD: 24.82) for the single-speech, 156.13 (SD: 24.77) for the one-distractor, and 160.39 (SD: 23.30) for the two-distractor condition. For distractor numerals and syntactic violations the average number of artifact-free trials were 179.26  and 74.13  for the one-distractor condition, 171.17  and 72.52  for the two-distractor male, and 184.26  and 72.30  for the two-distractor female speaker.Post-hoc tests were conducted for all main effects and interactions that included the CONDITION (for targets) or the DISTRACTOR (for distractors) factor by Tukey’s HSD. Greenhouse–Geisser correction of sphericity violations was employed where applicable and the ε correction factor is reported together with the η2 effect size. Only significant effects including the CONDITION/DISTRACTOR factor are reported in the main text  × ANTERIOR-POSTERIOR  × LATERALITY , separately for the N2 and P3 components. Distractor ERPs and ERPs for syntactic violations were analyzed similarly, using repeated-measures ANOVAs with the factors of DISTRACTOR  × ANTERIOR-POSTERIOR  × LATERALITY , separately for the N2 and P3 components. F = 12.246, p < 0.001]. This was due to the significantly lower memory performance in the single-speech condition compared to both the one- (p < 0.001) and the two-distractor (p = 0.011) conditions, whereas the latter two did not significantly differ from each other (p = 0.161). No significant effects were found for the reaction times (p = 0.633), hit (p = 0.123), and false alarm rates (p = 0.676), while a marginally significant effect was obtained for detection sensitivity (p = 0.074).The descriptive statistics of the behavioral performance are shown in F = 19.200, p < 0.001]. The effect was caused by the significantly lower distractor effect of the numerals spoken by the two-distractor female speaker compared to the one- and two-distractor male speaker . The latter two were not significantly different from each other (p = 0.225).A significant effect of DISTRACTOR was found on the distraction effect [p < 0.001, df = 2). Post hoc significance values were adjusted by the Bonferroni correction for multiple tests, showing that significantly larger confidence judgment occurred in the one-distractor condition compared to the single-speech and two-distractor conditions  whereas these were not different from each other (p = 1.00).The confidence judgment was significantly different between the three conditions  = 2.862; ε = 0.799; p = 0.0398; Post-hoc tests showed that the N2 amplitude significantly differed between all three conditions  on the left side : the largest N2 amplitude was observed for one-distractor which decreased for single-speech with the lowest amplitude for two-distractor (best seen on p = 0.88) or on the right side (p = 1.00) with those for two-distractor condition significantly differing from both at the midline . In all of these cases, the amplitude for the target N2 was lower for two-distractor condition than for single-speech and one-distractor condition. A significant main effect of CONDITION was found for the P3 component [F = 18.580; ε = 0.987 p < 0.001; F = 3.973; ε = 0.827; p = 0.009; F = 2.575; ε = 0.638; p = 0.029; post hoc analysis, a separate ANOVA was conducted on the parietal line, alone, with the factors of CONDITION and LATERALTY. In this post hoc analysis, main effects of CONDITION [F = 15.956; ε = 0.859; p < 0.001; F = 13.921; ε = 0.763; p < 0.001; p = 0.292). The post-hoc test of the CONDITION main effect showed significantly lower amplitudes for single-speech condition compared to one-distractor and two-distractor , while the latter two were not significantly different from each other (p = 0.204).For target events, significant interaction was found for the N2 amplitude between CONDITION and LATERALITY [r = −0.009; p = 0.966), one-distractor , and two-distractor conditions .Based on the similar pattern between the recognition performance data and P3 amplitude in the three conditions, Pearson correlation was calculated between them, using the P3 measured at the Pz electrode. No significant correlation was found between the P3 amplitude and recognition performance in the single stream (p = 0.030), Cz (p = 0.021), and C4 (p = 0.018) electrodes for distractor numerals appearing in the male-spoken stream of the two-distractor condition. No other distractor numeral or syntactic violation ERP amplitudes differed significantly from zero in the N2 latency range . In the P3 time window, ERP amplitudes significantly differing from zero were found for distractor numerals in the one-distractor condition , and for syntactic violations appearing in the male-spoken non-target speech stream in the two-distractor condition . No other distractor numeral or syntactic violation ERP amplitudes differed significantly from zero in the P3 latency range .Event-related potential amplitudes significantly different from zero were found in the N2 time window at the C3  = 3.429; ε = 0.547; p = 0.037; Post-hoc tests revealed that this interaction was due to the central ERP amplitude in the N2 time window for two-distractor male being more positive than that for one-distractor male centrally (p = 0.033), and also than one-distractor male and two-distractor female parietally . In contrast, no significant difference was found for the amplitudes from the N2 window between the one-distractor male and two-distractor female either over central (p = 0.491) or parietal electrode locations (p = 1.000). No other significant difference was found either in the N2 or the P3 time window.The positive deflection measured for the distractors in the N2 time window  = 3.774; ε = 0.908; p = 0.031; p > 0.067). Post-hoc test revealed that the main effect resulted from the more positive deflection for the two-distractor male than for the one-distractor male (p = 0.030) syntactic violations, whereas none of them was different from the two-distractor female (p > 0.133).Finally, there was no significant main effect or interaction for syntactic violations in the N2 time window , whereas allocation problems can be found when a speech stream is masked by another speech . The patients/participants provided their written informed consent to participate in this study.IW, GO, and BT contributed to the conception and design of the study. DF organized the database. OS performed the statistical analysis and wrote the first draft of the manuscript. BT and IW wrote sections of the manuscript. All authors contributed to the manuscript revision, read, and approved the submitted version.


Firstly, we investigated the compound’s affinity for 5-HT6 receptors and its functional activity by using in vitro assays. JJGW07 did not bind to 5-HT6 receptors and showed antagonistic properties for 5-HT1A, 5-HT2A, 5-HT7, and D2 receptors. Based on the receptor profile, we performed behavioral studies in mice to evaluate the antidepressant-like, anxiolytic-like, and antipsychotic-like activity of the tested compound using forced swim and tail suspension tests; four-plate, marble-burying, and elevated plus maze tests; and MK-801- and amphetamine-induced hyperlocomotion tests, respectively. JJGW07 revealed antidepressant-like properties in the tail suspension test, anxiolytic-like effects in the four-plate and marble-burying tests, and antipsychotic-like activity in the MK-801-induced hyperlocomotion test. Importantly, the tested compound did not induce catalepsy and motor impairments or influence locomotor activity in rodents. Finally, to assess the potential procognitive and anti-amnesic properties of JJGW07, we used passive avoidance and object recognition tests in mice. JJGW07 demonstrated positive effects on long-term emotional memory and also ameliorated MK-801-induced emotional memory impairments in mice, but showed no procognitive properties in the case of recognition memory. Our results encourage the search for new compounds among salicylamide derivatives, which could be model structures with multitarget mechanisms of action that could be used in psychiatric disorder therapy.Depression, anxiety, and schizophrenia may coexist in psychiatric patients. Moreover, these disorders are very often associated with cognitive impairments. However, pharmacotherapy of these conditions remains challenging due to limited drug effectiveness or numerous side effects. Therefore, there is an urgent need to develop novel multimodal compounds that can be used to treat depression, anxiety, and schizophrenia, as well as memory deficits. Thus, this study aimed to evaluate the potential antidepressant-like, anxiolytic-like, antipsychotic-like effects, and anti-amnesic properties, of the novel arylpiperazine derivative of salicylamide, JJGW07, with an affinity towards serotonin 5-HT Depression, anxiety, and schizophrenia may coexist in psychiatric patients. Moreover, these disorders are very often associated with cognitive impairments. Untreated or badly-diagnosed mental illnesses lead to a decreased quality of life, difficulties with social functioning, alcohol or drug addictions, and a higher risk of suicide . UnfortuUnfortunately, despite numerous antipsychotics, antidepressants, and anxiolytics on the market, many patients do not respond to treatment. Furthermore, the available therapeutic options have many side effects, which are often a reason for drug discontinuation. Therefore, considering the limited effectiveness and safety of the available therapeutics, searching for novel drugs that improve the pharmacotherapy of mental disorders is one of the leading health challenges of the 21st century.1A, moderate affinity for 5-HT7 and D2, and weak affinity for 5-HT2A receptors butoxy}benzamide hydrochloride, JJGW07, was synthesized in the Department of Organic Chemistry and Technology, Faculty of Chemical and Engineering and Technology, Cracow University of Technology. The synthesis and biological properties of the compound were described earlier [ip) 30 min before each behavioral test. The chemicals used in the radioligand studies, i.e., methiothepin , were dissolved in saline. MK-801  was dissolved in saline and administered ip 15 min before experiments, whereas amphetamine  was dissolved in saline and administered subcutaneously (sc) 30 min before tests. Aripiprazole  was dissolved in 1% Tween  and administered ip 30 min before experiments. The control groups received 0.9% NaCl solution or 1% Tween as a vehicle. The tested compound was administered at the dose range of 0.625–2.5 mg/kg. The dose range was chosen based on our previous experiments on salicylamide derivatives [JJGW07 was dissolved in saline  and administered intraperitoneally  in a controlled environment , adequate humidity (40–60%), and a 12 h light/dark cycle), with ad libitum access to food and water. Behavioral procedures were performed between 8 a.m. and 4 p.m. by a trained observer blind to the treatments. Animals were selected randomly for the treatment groups. Each group consisted of 8–10 mice that were used only once in each test and were euthanized immediately after the experiments. All injections were administered in a 10 mL/kg volume. Procedures involving animals were conducted according to the current European Community and Polish legislation on animal experimentation.6 receptor. The assay procedures were conducted according to a slightly modified method described by Sałaciak and colleagues [Radioligand binding assays were performed using membranes from CHO-K1 cells, which were stably transfected with the human 5-HTlleagues .–10 to 10–5 M. The inhibitory constant (Ki) was estimated using GraphPad Prism 5.0 . A single assay was performed with each compound concentration in duplicate, and the whole assay was repeated in three independent experiments. Inhibition constants (Ki) were calculated according to the equation of Cheng and Prusoff [Binding experiments were conducted in 96-well microplates, and the reaction mix included a solution of the test compound, radioligand, and diluted membranes or the tissue suspension. Specific assay conditions for each target are shown in  Prusoff .1A, 5-HT2A, and D2 receptors, human GPCR, the promiscuous G protein Gαqi/5 for the D2 receptor, and α16 for 5-HT1A and 5-HT2A . The assay was executed according to a previously described protocol [1A receptor, 30 nM α-methylserotonin for the 5-HT2A receptor, and 30 nM apomorphine for the D2 receptor) was equal to EC80. IC50 and EC50 values were calculated.Tested and reference compounds were dissolved in dimethyl sulfoxide (DMSO) at a concentration of 10 mM. Serial dilutions were prepared in a 96-well microplate in an assay buffer, and 8 to 10 concentrations were tested. An intrinsic activity assay was performed according to the manufacturer of the ready-to-use CHO-K1 cells with the stable expression of the human serotonin 5-HTprotocol . After t7 receptor, the adenylyl cyclase activity was monitored using cryopreserved CHO-K1 cells with expression of the human serotonin 5-HT7 receptor. A functional assay based on cells with expression of the human 5-HT7 receptor was performed, according to a previously described protocol [Test and reference compounds were dissolved in DMSO at a concentration of 1 mM. Serial dilutions were prepared in a 96-well microplate in the assay buffer and 8 to 10 concentrations were tested. For the 5-HTprotocol . CHO-K1 50 and EC50 values were calculated by a non-linear regression analysis using GraphPad Prism 5.0 software. The log IC50 was used to obtain the Kb by applying the Cheng–Prusoff approximation.Thawed cells were resuspended in a stimulation buffer  at 200,000 cells/mL. The same volume (10 μL) of cell suspension was added to tested compounds loaded onto a white opaque half-area 96-well microplate. The antagonist response experiment was performed with 10 nM serotonin as the reference agonist. The agonist and antagonist were added simultaneously. Cell stimulation was performed for 60 min at room temperature. After incubation, cAMP measurements were performed with a homogeneous TR-FRET immunoassay using the LANCE Ultra cAMP kit . Then, 10 μL of EucAMP Tracer Working Solution and 10 μL of ULight-anti-cAMP Tracer Working Solution were added, mixed, and incubated for 1 h. The TR-FRET signal was read on an EnVision microplate reader . ICThe experiment was performed on mice according to the method described by Porsolt et al., and as previously described ,83. MiceThe experiment was carried out on mice according to the method described by Steru et al., and as previously described ,84. The The four plate test was performed on mice according to a previously described method ,86. MiceThe test was conducted according to the method described by Broekkamp et al.  with minThe elevated plus maze was performed according to a method previously described ,19. The The locomotor activity of mice was measured as previously described . The mob50 value was calculated as the dose at which 50% of the animals could not stay on the rotating rod [The experimental procedure has been described in detail by Pytka K. et al. . Mice weting rod .ip) and one of amphetamine  or MK-801 . Control groups received either an injection of saline and amphetamine or MK-801, or two injections of saline.The test was performed according to the method described by Carlsson et al. ,90, usin-Score of 0 points if the animal held the constrained position for <15 s;-Score of 1 point if the animal stayed on the bar for 15–29.9 s;-Score of 2 points if the animal stayed on the bar for 30–59.9 s;-Score of 3 points if the animal stayed on the bar for more than 60 s.Catalepsy was assessed using the bar method described by Ueki et al. with minor modifications ,92. The ip 30 min before the acquisition trial. To induce memory impairments, MK-801 (0.125 mg/kg) was administered ip 15 min before the experiment. Control groups were injected ip with saline/1% Tween or with saline/1% Tween and MK-801.The step-through passive avoidance task was performed according to a method previously described ,93. The ip 30 min before the familiarization phase to assess their influence on recognition memory. To induce memory disturbances, MK-801 (0.125 mg/kg) was administered ip 15 min before the experiment. Control groups were injected ip with saline/1% Tween or with saline/1% Tween and MK-801.The test was performed according to the method described earlier ,94 and ct-test was used to analyze the results of the object recognition task. In cases when assumptions for a normal distribution of data were not fulfilled, we used a Kruskal–Wallis with Dunn’s post hoc test. A value of p < 0.05 was considered to be significant.The results are presented as means ± SD (standard deviation) or medians with an interquartile range . The normality of data sets and their homogeneity were determined using D’Agostino and Pearson and Brown–Forsythe tests, respectively. The comparisons between experimental and control groups were performed by one-way ANOVA followed by a Newman–Keuls post hoc test or two-way ANOVA with repeated measures followed by a Bonferroni post hoc test. A one-sample 2 and serotonin 5-HT1A receptors, very weak properties at serotonin 5-HT2A and 5-HT7 receptors, and no affinity towards 5-HT6 receptors. The tested compound showed antidepressant-, anxiolytic-, and antipsychotic-like properties in rodents. Furthermore, JJGW07 did not affect the locomotor coordination or induce catalepsy in mice at antipsychotic-like doses. Moreover, JJGW07 displayed procognitive and anti-amnesic properties in mice. Overall, our observations suggest that JJGW07 could be a model structure for the synthesis of new derivatives of salicylamide with potential use in the treatment of psychiatric disorders such as depression, anxiety, schizophrenia, and memory deficits.In this study, we evaluated the basic pharmacological profile of JJGW07, a novel arylpiperazine alkyl derivative of salicylamide, which demonstrated strong antagonistic properties at dopamine D


Cured elastomers were characterized using FT-IR, DSC, TGA, mechanical testing, and contact angle measurement. In vitro enzymatic degradation of PGSE over a period of 28 days was investigated. FT-IR spectroscopy confirmed the formation of peptide bonds. The glass transition temperature for the elastomer was found to increase as the ratio of sebacic acid/glutamic acid was increased to four. The decomposition temperature of the elastomer decreased as the amount of glutamic acid was increased. PGSE exhibited less stiffness and larger elongation at break as the ratio of sebacic acid/glutamic acid was decreased. Notably, PGSE-Z was stiffer and had smaller elongation at break than PGSE and PGSE-B at the same molar ratio of monomers. The results of in vitro enzymatic degradation demonstrated that PGSE has a lower degradation rate than does PGS, whereas PGSE-B and PGSE-Z degrade at a greater rate than does PGS. SEM images suggest that the degradation of these crosslinked elastomers is due to surface erosion. The cytocompatibility of PGSE was considered acceptable although slightly lower than that of PGS. The altered mechanical properties and retarded degradation kinetics for PGSE reflect the influence of peptide bonds formed by the introduction of L-glutamic acid. PGSE displaying a lower degradation rate compared to that for PGS can be used as a scaffold material for the repair or regeneration of tissues that are featured by a low healing rate.Poly(glycerol sebacate) (PGS), a soft, tough elastomer with excellent biocompatibility, has been exploited successfully in many tissue engineering applications. Although tunable to some extent, the rapid in vivo degradation kinetics of PGS is not compatible with the healing rate of some tissues. The incorporation of L-glutamic acid into a PGS network with an aim to retard the degradation rate of PGS through the formation of peptide bonds was conducted in this study. A series of poly(glycerol sebacate glutamate) (PGSE) containing various molar ratios of sebacic acid/L-glutamic acid were synthesized. Two kinds of amino-protected glutamic acids, Boc-L-glutamic acid and Z-L-glutamic acid were used to prepare controls that consist of no peptide bonds, denoted as PGSE-B and PGSE-Z, respectively. The prepolymers were characterized using  Tissue engineering integrates cells, biodegradable scaffolds, growth/stimulating factors or their combinations to restore, maintain, or improve damaged tissues or whole organs . SpecifiPolyester is one of most frequently used biodegradable polymers in tissue engineering. Thermoplastic polyesters such as poly(lactic acid) (PLA), poly(glycolic acid) (PGA), polycaprolactone (PCL) and their copolymers have been widely used in biomedical applications due to their biocompatibility, biodegradability and ease of processing . The mecPGS is a biodegradable elastomer synthesized by condensation of glycerol and sebacic acid , both ofPGS scaffolds are conventionally fabricated by solvent casting followed by curing and salt leaching. Mechanically anisotropic PGS scaffolds have been prepared using microfabrication techniques  or alignin vitro degradation studies involving no enzymes [PGS is resorbed completely within 60 days after subcutaneous implantation in rats . The fas enzymes ,26. The  enzymes , could rThe functional groups of glycerol and sebacic acid can react with those of other monomers and thus offer unlimited possibilities for the generation of new crosslinked polymers for specific purposes. For example, the introduction of lactic acid into a PGS network modulates the microstructure of PGS analogues, and hence the degradation rate and mechanical properties , whereasPoly(ester amide)s that integrate the excellent thermal and mechanical properties of polyamides with the biocompatibility and biodegradability of polyesters have gained increasing attention for medical applications, including use as scaffolds for tissue engineering ,39,40. I6 (DMSO-d6) and tetramethylsilane were purchased from Sigma-Aldrich . Sebacic acid was purchased from ACROS . L-glutamic acid was purchased from Alfa Aesar . Boc-L-glutamic acid and Z-L-glutamic acid were purchased from Bachem . Acetone andtetrahydrofuran (THF) were purchased from Macron . For cell culture, Dulbecco’s modified Eagle’s medium (DMEM), penicillin/streptomycin, and trypsin-EDTA were obtained from Thermo Fisher Scientific  and calf serum was purchased from Hyclone . WST-8 assay was purchased from Abbkine . All chemicals were used as received without further purification.Glycerol, dimethyl sulfoxide-d1H NMR was used to characterize the chemical structure of the prepolymers. The prepolymers were dissolved in DMSO-d6 to prepare 20 mg/mL solutions. 1H NMR spectra were recorded on an Avance 600 MHz NMR spectrometer . Chemical shifts were given in ppm with tetramethylsilane as a standard. Gel permeation chromatography was performed to estimate the molecular weight of the prepolymers. A Shimadzu modular system with an autosampler and a differential refractive index detector was used. Three Shodex LF-604 columns  were employed in series. The prepolymers were dissolved in THF to prepare 3 mg/mL solutions, which were filtered before injection. The mobile phase was THF at 40°C with a flow rate of 0.3 mL/min. Calibration was achieved by monodisperse polystyrene standards ranging from 1.31 to 71.8 kg/mol.Prepolymers for poly(glycerol-sebacate-glutamate) (PGSE), poly(glycerol-sebacate-Boc-glutamate) (PGSE-B), poly(glycerol-sebacate-Z-glutamate) (PGSE-Z) were prepared based on the method developed by Wang et al.  with modw/v) solution. The solution was poured into a PTFE mold. Acetone was then removed by placing the mold on a 60°C heater. Upon the removal of acetone, the prepolymer in the mold was cured in a vacuum oven at 150°C under 0.1 Pa for 48 h.To prepare elastomer films from prepolymers, the prepolymer was first dissolved in acetone to make a 30%  with an ATR module.The chemical structure of the cured PGS, PGSE, PGSE-B, and PGSE-Z was examined by infrared spectroscopy. Fourier transform infrared (FT-IR) spectra of the elastomers were obtained by scanning the specimens for 64 times in the wave number range from 600–4000 cmDifferential scanning calorimetry (DSC) was performed with a Q20 differential scanning calorimeter . Samples of PGS, PGSE, PGSE-B, and PGSE-Z weighing ~3 mg were used. The experiments were conducted at a heating rate of 10 °C/min from −60 to 150°C. The sample chamber was purged with nitrogen gas at a rate of 15 mL/min. The thermal stability of the elastomers was examined by a TGA 4000 Thermogravimetric Analyzer . Samples weighing ~12 mg were subjected to a ramp rate of 10 °C/min from 25 to 600°C. The decomposition temperature is defined as the temperature at which the remaining weight reaches 95% of the initial dry weight.−1. The deformation of the specimen was assessed by tracking the positions of twelve markers attached on the central region of the specimen with respect to their positions in the unloaded configuration and presented in terms of stretch ratio in the stretching direction. The thickness of the specimen was measured by the high-frequency ultrasound system. Given the deformation and the thickness of the specimen, Cauchy stress can be calculated based on tensile force recorded by the load cell. From the stress–stretch curve of the specimen, the Young’s modulus, the ultimate strength, and the elongation at break were determined (n = 5–6).Uniaxial tensile testing was performed using a custom-made mechanical tester  equippedThe wettability of PGS, PGSE, PGSE-B and PGSE-Z films was assessed by water contact angle measurements. Water drops of 5 µL were carefully deposited on the surface of the specimens by a micro-pipette. Images of the droplets on the surface were acquired by a digital camera  and the contact angles were measured by ImageJ  with an average of 6 measurements for each group.day 0) and sterilized with 70% ethanol followed by drying under UV irradiation in a laminar flow hood overnight. The disk was immersed in a 1.5-mL lipase solution (600 U/mL) and incubated at 37°C in a CO2 incubator . After incubation for 2, 7, 14, 21, and 28 days, the disk was removed, washed with deionized water, and dried under vacuum. After weighing (giving a weight Wday i), the disk was placed in a new lipase solution. The remaining weight percentage was calculated using the following formula:day iW represents the dry weight on day i; i= 2, 7, 14, 21, or 28, day 0W is the initial dry weight. The surface morphology of the sample was examined on day 0, 7, and 24 by scanning electron microscopy. Pieces of dry samples were mounted onto stubs, sputter-coated with platinum , and viewed in a scanning electron microscope .Disk samples of diameter of 6 mm were punched out of ~500-µm thick elastomeric films. The disk was weighed . The viability of the cells was presented as ODsample—ODblank where ODsample and ODblank are the absorbance of the test wells containing WST-8 reduced by the cells that were cultured with the specimen and that containing unreacted WST-8, respectively. At least 4 specimens for each group were analyzed. The cells after the WST-8 assay were fixed by 4% formaldehyde and immune-stained for GAPDH . Cell images were acquired using a fluorescence microscope  equipped with a CMOS camera .NIH/3T3 cells were cultured in direct contact with the elastomer specimens to assess the Data are presented as mean ± standard deviation. Differences in mechanical properties and cytocompatibility were analyzed by one-way ANOVA in conjunction with Tukey post hoc procedure. The level of significance was set at 0.05.1H-NMR spectroscopy. 1H-NMR spectra of the prepolymers with each peak assigned. The peaks at δ 1.23, 1.48, and 2.26 ppm suggested that sebacic acid was included in all of the prepolymers. The peaks at δ 3.3–4.4 ppm indicated protons on unesterified glycerol, whereas the peaks at δ 4.6-5.3 ppm indicated protons on esterified glycerol. PGSE-B had a unique peak at δ 1.38 ppm and PGSE-Z had another unique peak at δ 7.34 ppm, which indicated the proton in the tert-butyl group and benzene, respectively. Note that the crosslinking reactions occurred randomly and it is not realistic to predict the exact structure of the prepolymers.The structure of the prepolymers of PGS, PGSE3, PGSE-B, and PGSE-Z was analyzed by The molecular weight of the prepolymers are listed in −1 in the spectra of PGSE2 and PGSE3 indicated secondary amine stretching; notably, PGSE1 did not display the peak and neither did PGSE-B and PGSE-Z. The peak at 1160 cm−1 attributed to the C-N stretching of amide was obvious in PGSE2 and PGSE3. The peak at 1735 cm−1 associated with the C=O stretching of ester was observed in all the elastomers. PGSE2 and PGSE3 exhibited a peak at 1690 cm−1, which corresponded to the C=O stretching of amide. The results suggested the formation of peptide bonds between L-glutamic acid and sebacic acid.The structure of the cured PGS, PGSE3, PGSE-B, and PGSE-Z was analyzed by FT-IR spectroscopy and the results are shown in Tg) of all the elastomers was below room temperature, which indicates that all the elastomers are in a rubbery state at room temperature or under physiological conditions. PGSE1 and PGSE2 had a slightly lower Tg compared to PGS. The reduction in Tg might be attributed to the compromised crystallinity of the prepolymer caused by the addition of a small amount of L-glutamic acid. Notably, further reducing the molar ratio of sebacic acid/glutamic acid significantly increased the Tg; PGSE3 had a significantly higher Tg compared to PGS. Furthermore, it should be noted that PGSE-B and PGSE-Z had a Tg comparable to PGS.DSC was used to examine the glass transition temperature of PGS, PGSE1, PGSE2, PGSE3, PGSE-B, and PGSE-Z. The mechanical behaviors of the elastomers are shown in Scaffold materials for tissue engineering should have proper surface hydrophilicity for cells to adhere. in vitro enzymatic degradation are shown in in vitro degradation was performed with the elastomers in the form of solid films. The degradation of porous scaffolds may be different due to the presence of porosity. Recently, the porosity and curing temperature were found to affect the PGS degradation kinetics [Past studies showed that PGS was completely degraded 42 to 60 days after implantation in rats ,45. To bkinetics .The cytocompatibility of PGS, PGSE1, PGSE2, PGSE3, PGSE-B, and PGSE-Z is shown in PGSE developed in this study can be used to repair or regenerate soft tissues that are subjected to a mechanically active environment and have a low healing rate such as cardiac muscles. It can also be exploited in the development of a drug delivery platform for the cases in which a longer release profile is desired.in vitro enzymatic degradation demonstrated that PGSE has a lower degradation rate than does PGS whereas PGSE-B and PGSE-Z degrade at a greater rate than does PGS. The cytocompatibility of PGSE was considered acceptable although slightly lower than that of PGS. The altered mechanical properties and retarded degradation kinetics of PGSE reflect the influence of peptide bonds formed by the introduction of L-glutamic acid. We conclude that PGSE can be used as a scaffold material for the repair or regeneration of tissues that are featured by a low healing rate.PGSE that contains peptide bonds in a crosslinked network was successfully synthesized by melt polycondensation of glycerol, sebacic acid, and L-glutamic acid. The incorporation of L-glutamic acid resulted in a network that was less stiff and had larger elongation at break. Notably, PGSE-Z was stiffer and had a smaller elongation at break than PGSE and PGSE-B, presumably due to π-π stacking interactions. The results of